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Machine Learning Engineer Jobs in Hayward, CA (NOW HIRING)

The company is driven by research and engineering that bridge cutting-edge machine learning with practical, scalable applications. Team members collaborate across disciplines to design systems that ...

New

NR Consulting is a company focused on innovative technology solutions, and they are seeking a Machine Learning Engineer to develop and deploy lightweight machine learning models for edge AI ...

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to core technology and product features.

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of key technologies and ...

The Machine Learning Engineer will play a central role in building the core technology for training, evaluating, and deploying interpretable frontier AI systems, contributing to tools, infrastructure ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

They are seeking Machine Learning Engineers to develop their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to various aspects such as ...

They are seeking a Machine Learning Engineer to contribute to the development of tools and infrastructure for interpretable AI systems, playing a key role in transforming research into usable product ...

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Showing results 21-40

Machine Learning Engineer information

See Hayward, CA salary details

$36.1K

$147.6K

$221.8K

How much do machine learning engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for machine learning engineer in Hayward, CA is $147,633.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,400.00 and $177,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Hayward, CA?

The most popular types of Machine Learning Engineer jobs in Hayward, CA are:

What are popular job titles related to Machine Learning Engineer jobs in Hayward, CA?

For Machine Learning Engineer jobs in Hayward, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Hayward, CA look for?

The top searched job categories for Machine Learning Engineer jobs in Hayward, CA are:

What cities near Hayward, CA are hiring for Machine Learning Engineer jobs?

Cities near Hayward, CA with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Hayward, CA as of August 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $147,633 per year, or $71 per hour.

Machine Learning Engineer

RZR Global Inc.

San Francisco, CA

Full-time

Re-posted 17 days ago


Job description

Who are we?

RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.

Role Overview

We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.

Key Responsibilities
  • Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.

  • Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.

  • Analyze the impact of integrating new data sources and features into our models.

  • Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.

  • Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.

  • Document experiments, assumptions, and outcomes; maintain reproducibility

Required Skills / Experience
  • Bachelor's or Master's degree in Mathematics, Physics, Computer Science, or a related technical field.

  • At least 1 year of professional experience in machine learning, statistical analysis, and data analysis.

  • Experience with machine learning techniques such as regression, classification, and clustering.

  • Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).

  • Strong grasp of probability, statistics, and data analysis principles.

  • Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.

Nice-to-Have
  • Familiarity with system programming languages including C++ and Rust is a plus.

  • Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)

  • Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.